Lovelace, R orcid.org/0000-0001-5679-6536, Birkin, M, Cross, P et al. (1 more author) (2016) From Big Noise to Big Data: Toward the Verification of Large Data sets for Understanding Regional Retail Flows. Geographical Analysis, 48 (1). pp. 59-81. ISSN 0016-7363
Abstract
There has been much excitement amongst quantitative geographers about newly available datasets, characterised by high volume, velocity and variety. This phenomenon is often labelled as 'Big Data' and has contributed to methodological and empirical advances, particularly in the areas of visualisation and analysis of social networks. However, a fourth v - veracity (or lack thereof) - has been conspicuously lacking from the literature. This paper sets out to test the potential for verifying large datasets. It does this by cross-comparing three unrelated estimates of retail flows --- human movements from home locations to shopping centres --- derived from the following geo-coded sources: 1) a major mobile telephone service provider; 2) a commercial consumer survey; and 3) geotagged Twitter messages.
Three spatial interaction models also provided estimates of flow: constrained and unconstrained versions of the 'gravity model' and the recently developed 'radiation model'. We found positive relationships between all data-based and theoretical sources of estimated retail flows. Based on the analysis, the mobile telephone data fitted the modelled flows and consumer survey data closely, while flows obtained directly from the Twitter data diverged from other sources. The research highlights the importance of verification in flow data derived from new sources and demonstrates methods for achieving this.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 The Authors. Geographical Analysis published by Wiley Periodicals, Inc. on behalf of The Ohio State University. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | big data; verification; gravity model; spatial interaction |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Funding Information: | Funder Grant number ESRC ES/L011891/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Sep 2015 10:58 |
Last Modified: | 23 Jun 2023 21:52 |
Published Version: | http://dx.doi.org/10.1111/gean.12081 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/gean.12081 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:90001 |